Regulation and Antitrust - Johannes Kepler University of Linz · 2011-04-11 · Regulation and...
Transcript of Regulation and Antitrust - Johannes Kepler University of Linz · 2011-04-11 · Regulation and...
Regulation and AntitrustCollusion and horizontal agreements
Christine Zulehner
Department of EconomicsJohannes Kepler University Linz
Summer term 2011
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Motivation
Adam Smith (1776) already noticed that
� people of the same trade seldom meet together, even for merrimentand diversion, but the conversation ends in a conspiracy against thepublic, or in same contrivance to raise prices ....
Illustration: newspaper industry in Detroit
� in 1989, Detroit Free Press and Detroit News were allowed to mergealthough they formed a monopoly as Free Press was about to fail
� the two papers further appeared as two entities, but the firm mergedon all other aspects like cost, setting rates, advertising and so on.
� firm acted as a monopoly and we observed a change in profits: eachlost about 10 Mill. a year, afterwards profits were high as 150 Mill
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Incentive to collude
Linear demand: p = a − b ∗ q and constant marginal cost: MC = c
Monopoly
� maximize: π = (p − c) ∗ q = (a − bq − c) ∗ q� FOC: dπ
dq = a − 2b ∗ q − c = 0 → q = a−c2b and p = a+c
2
� πM = (a−c)2
4b
Cartel of two firms i = 1, 2: πCarteli = (a−c)2
8b
Cournot competition among two firms i = 1, 2
� maximize π1 = (a − b ∗ (qi − q2) − c) ∗ q1
� FOC: dπ1
dq = a − 2b ∗ q1 − b ∗ q2 − c = 0
� → q1 = a−c3b = q2, q = 2(a−c)
3b and p = a+2c3
� πCournoti = (a−c)2
9b
Price competition among two firms i = 1, 2: πBertrandi = 0
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Outline
Collusion and cartels
Collusion theory
Factors that facilitate collusion
Policies against collusion
Calculation of cartel damages
Literature
� chapter 4 in Motta (2004): Competition policy: Theory and practice� chapter 7 in Davis and Garces (2010): Quantitative techniques for
competition and antitrust analysis
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Collusion and cartels
What is collusion?
� since total industry profits in oligopoly are always lower than monopolyprofits, firms will attempt to establish agreements among each other toeliminate competition
What is a cartel?
� institutional form of collusion� attempt to enforce market discipline and reduce competition between a
group of suppliers� cartel members agree to coordinate their actions (prices fixing, quotas,
consumer allocation, bid rigging)� prevent excessive competition between the cartel members� secret agreements, because cartels illegal in the US and EU
Tacit collusion: mutual understanding without explicit agreement
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Incentives to cheat
Main problem with cartel agreements as well as tacit collusion
� temptation to cheat on competitors� if all other firms stick to the agreement, you can increase profits by
deviating and stealing your rivals’ business (undercutting, violatingterritories, etc)
� comparable to a Prisoner’s dilemma
To sustain collusion, cartel must be able to
� detect deviators: can you give an answer to a question like “Have pricesdecreased as someone deviated or as demand decreased?”
� punish the deviator(s): which strategies are possible?
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The diamond cartel
De Beers established in South Africa in 1888 by Cecil Rhodes
� owned all diamond mines in South Africa� had joint ventures in Namibia, Botswana, Tanzania� controlled diamond trade (mines → cutters and polishers) through
“Central Selling Organization” (CSO), processing about 80% of worldtrade
CSO’s services for the industry
� expertise in classifying diamonds� stabilizing prices (through stocks of diamonds)� advertising diamonds
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The diamond cartel cont’d
Huge temptation for mining companies to bypass CSO and earn highmargins themselves
In 1981, President Mobutu announced that Zaire (world’s largest supplier ofindustrial diamonds) would no longer sell diamonds through the CSO
Two months later, about 1 million carats of industrial diamonds flooded themarket, price fell from $3 to less than $1.80 per carat
Supply of these diamonds unknown, but very likely retaliation by De Beers
In 1983, Zaire renewed contract with De Beers, at less (!) favorable termsthan before
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The law
Cartel laws make cartels nowadays illegal in the US and Europe
� US: jail sentences (DRAM cartel)� exception in the US: export cartels� exception in Austria: “Bagatellkartelle”
Cartels have always been with us and still are
Some are explicit and difficult to prevent (OPEC)
Other less explicit attempts to control competition
Authorities continually search for cartels
� improving methods detecting cartels like price screening� leniency programs� have been successful in recent years (nearly $1 billion in fines in 1999)
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The vitamin cartel
EC has found that 13 European and non-European companies participatedin cartels aimed at eliminating competition in the vitamin A, E, B1, B2, B5,B6, C, D3, Biotin (H), Folic Acid (M), Beta Carotene and carotinoidmarkets.
A striking feature of this complex of infringements was the central roleplayed by Hoffmann-La Roche and BASF, the two main vitamin producers,in virtually each and every cartel, whilst other players were involved in only alimited number of vitamin products → severity of punishment
Firm Country Fines in mill AC
Hoffman-La Roche AG Switzerland 462.00BASF AG Germany 296.00Aventis SA France 5.04Solvay Pharmaceuticals Netherlands 9.10Merck KgaA Germany 9.24Daiichi Pharmaceuticals Co Ltd Japan 23.40Eisai Co Ltd Japan 13.23Takeda Chemical Industries Ltd Japan 37.05
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Collusion theory
Noncooperative collusion in a static model vs. repeated games
� dominant firm model� dynamic strategies
Factors that facilitate collusion
� market structure� price transparency and exchange of information� pricing rules (facilitating practices)
Further reading
� imperfect information and non-cooperative collusion (Greene andPorter 1984)
� price wars during booms (Rotemberger and Saloner 1986)� impact of cyclical demand movements on collusive behavior
(Haltiwanger and Harrington 1986)� collusion with capacity constraints (Fabra 2006)
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Noncooperative collusion in a static model
N firms produce a homogenous product
let the inverse demand function be linear
� p = a − bQ with Q =∑N
i=1 qi
constant average and marginal cost
� c(qi) = c
F of the N firms form the fringe
each firm in the fringe acts as a Cournot quantity setting oligopolist
� it maximizes its own profit taking the the output of the other firms asgiven
the remaining K firms restrict output and maximize joint profits taking thebehavior of the fringe into account
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Noncooperative collusion in a static model
profit maximization
� maxπj = pqj − cqj = (a − bQ)qj − cqj
� FOC:∂πj
∂qj= (a − bQ) − bqj − cqj = 0
� → 2bqj = a − c − bQK − bQF−j
each fringe firm selects output along a best-response curve
� qj = 12 (S − QK − bQF−j)
� with S = a−cb and QK =
∑Kk=1 qk the output of the restrictive group
� QF−j is the combined output of all fringe firms except firm j
in equilibrium all fringe firms produce the same output
� QF−j = (F − 1)qj
� qj = 12 (S − QK − bQF−j)
� qj = S−QK
F−1 and QF = F S−QK
F+1
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Noncooperative collusion in a static model
residual demand function the restrictive group is facing
� p = a − b(QK − QF )� p = c + b
F+1 (S − QK )
profit maximization
� maxπk = pqk − cqk
given residual demand, the profit maximizing per firm and total output are
� qk = 1K
12S and QK = 1
2S
the output restricting group acts as Stackelberg leader
� qf = 1F+1
12S and p = c + 1
F+112bS
profits per firm of firms inside and outside the restrictive group
� πk(F , K ) = bK(F+1)
12S and πf (F ) = b
(F+1)2 (12S)2
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Noncooperative collusion in a static model
questions: is this a stable situation? is there an incentive to deviate?
assume first, all firms restrict output
� such a situation is stable if� πk(0, N) ≥ πf (1) → N ≤ 4� if there are four or less than four firms then output restriction is stable;� if there are more than four firms that restrict output, each firms share
of the monopoly profit is too small; each firms should defect and act asan independent Cournot firm
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Noncooperative collusion in a static model
if the number of fringe firms is positive, the conditions for internal andexternal stability can be rewritten as
� F + 1 + 1F ≤ K ≤ F + 3 + 1
F+1� necessary and sufficient condition for internal stability: no restricting
firm wants to deviate� necessary and sufficient condition for external stability: no fringe firm
wants to deviate
� enough firms in the fringe so that fringe profits are not too great andoutput restricting firms have no incentive to join the fringe
� enough firms restricting output so that fringe firms do not want to jointhe output restricting firms
� since F and K are integers, this implies that if there are F firms in thefringe, output restriction is stable only if output restriction is by groupsof F + 2 or F + 3 firms
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Noncooperative collusion in repeated games
static models omit an essential element of the cost of defecting from anoutput restricting equilibrium
� profit lost once rivals realize that the agreement is being violated
when firms deviate, the equilibrium output of all firms increases
other firms observe that and react by also deviating and producing moreoutput
whether output restriction is stable in a dynamic sense depends on a singlefirm’s present value of short-term gains from output expansion
firms compare future discounted profits to short-run gains due to deviation
such a trade-off cannot be analyzed in a static game
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Cartel stability
in general, cartels are unstable
can we find mechanisms that give stable cartels?
� violence is one possibility!� suppose that the firms interact over time� make cheating unprofitable: reward “good” behavior, punish “bad”
behavior
ingredients necessary to enforce collusion
� timely detection of deviations from collusive actions� credible mechanism for the punishment of deviations� threat of punishment prevents firms from deviating
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Incentive to deviate
Cournot with two firms i = 1, 2
� linear demand p = a − b ∗ (q1 + q2) and constant marginal cost c� maximize π1 = (a − b ∗ (q1 − q2) − c) ∗ q1
� FOC: dπ1
dq1= a − 2b ∗ q1 − b ∗ q2 − c = 0
� → q1 = a−c3b = q2 and p = a+2c
3
� profits: π1 = (a−c)2
9b = π2
firm 1 sticks to the collusive agreement and firm 2 deviates by playing a bestresponse
� profits of firm 1: πcollude1 = 3(a−c)2
8∗4b
� profits of firm 2: πdeviate2 = 9(a−c)2
8∗8b > πcollude1
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Repeated games
formalizing these ideas leads to repeated games
� a firm’s strategy is conditional on previous strategies played by the firmand its rivals
profits from cheating are taken into account
repeated games can become very complex
� strategies are needed for every possible history
but some “rules of the game” reduce this complexity
� Nash equilibrium reduces the strategy space considerably
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Finite vs. infinite games
number of periods played is known and finite
� credibility of punishment strategies and possibility of cooperationdisappears
� backward induction� Selten theorem: if a game with a unique Nash equilibrium is played
finitely many times, its solution is that Nash equilibrium played everytime
suppose the cartel expects to last indefinitely
� equivalent to assuming that the last period is unknown� every period there is a finite probability that competition will continue� now there is no definite end period� so it is possible that the cartel can be sustained indefinitely
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Noncooperative collusion in a repeated game
Intuition: cartels solve the cheating problem by threatening to punishdeviators in the future
� homogenous good duopoly� constant symmetric MC� in each period t = 1, 2, 3, . . . , firms simultaneously set prices� “repeated Bertrand game”
Equilibrium?
One possibility
� Bertrand equilibrium (i.e. p1 = p2 = MC) in each period t = 1, 2, 3, . . .
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Noncooperative collusion in a repeated game cont’d
Another possibility
� collusive equilibrium (p > MC)
Suppose firms play “grim trigger strategies”:
� in the first period, both firms set pM (monopoly price), and shareprofits πM equally.
� in any of the following periods: firm sets pM if both firms set pM ineach preceding period
� if instead one of the firms violated the collusive agreement (price belowpM in previous period), then both firms set p = MC forever(“punishment” or “retaliation”)
Is this enough to keep firms from cheating?
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Noncooperative collusion in a repeated game cont’d
If both firms stick to the collusive agreement, each has expected discountedprofits as
� 0.5πM + 0.5δπM + 0.5δ2πM + . . . = 0.5πM1
1−δ� where δ < 1 is the discount factor
If firm 1 deviates today:
� undercut firm 2, make profits πM today� from tomorrow onwards, p = MC, and so π = 0
→ Is collusion better than deviation?
� incentive constraint: 0.5πM1
1−δ ≥ πM + 0� which holds whenever δ ≥ δ∗ = 0.5� with δ∗ the critical discount factor
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State games
assume there is a sequence of discrete time points
� at each point in time firms play a static game� repeated game� example: Cournot
a strategy vector s∗ ∈ S = (S1, . . . , Sn), the strategy set, is anoncooperative equilibrium if each element of s∗ maximizes thecorresponding player’s payoff taking other elements of s∗ as given
πi (s∗) = maxsi∈Si πi (s
∗1 , . . . , s∗i−1, si , s
∗i+1, . . . , s
∗n ), i = 1, . . . , n
Friedman (1971) proofed the existence of an equilibrium
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Strategies in a state game
how does the firm react when, for example, another firm deviates from acartel behavior
strategies describe behavior of the firm
example: trigger strategies
� let sncc be the strategy of the noncooperative collusion, i.e. firmsrestrict their output
� let snash be the strategy that gives the Nash outcome, in our example:Cournot
a trigger strategy is then
� 1: each player begins by playing his or her part of sncc and continues todo as long as all other players do the same
� 2: revert to snash in the period following any defection from sncc andcontinue to play snash forever
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Profits in each period and future discounted profits
πi ,nash < πi ,ncc < πi ,defect
such a condition holds, if the static game is Cournot, the demand function islinear, marginal cost is constant and the same for all firms
and the sncc strategy means that each firm produces 1n of the
noncooperative collusive output
PDVi ,ncc = απi ,ncc + α2πi ,ncc + . . . = α1−απi ,ncc
� with α the discount factor
PDVi ,defect = απi ,defect + α2πi ,nash + . . . = απi ,defect + α2
1−απi ,nash
compare discounted profits from the period of defection onwards
wlog we assume that this is the first period
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Equilibrium
for a trigger strategy to be a noncooperative equilibrium, the payoff functionadhering to the trigger strategy must be at least as great as the payoff fromdefection, i.e. PDVi ,ncc ≥ PDVi ,defect
PDVi ,ncc ≥ PDVi ,defect if α ≥ πi,defect−πi,ncc
πi,defect−πi,nash
or using α = 11+r if 1
r ≥ πi,defect−πi,ncc
πi,defect−πi,nash
this is always fulfilled, if r is sufficiently close to zero
or, α is sufficiently close to one, i.e. the future has the same importance asthe presence
if α is large enough, collusion can be sustained
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Equilibrium
one can also show that the equilibrium is subgame perfect
the result is that the trigger strategy sustains output paths that allow eachplayer to earn more than with Cournot output
example of Folk Theorem
� states that noncooperative behavior can sustain any strategy producingindividual profits larger than Nash profits, if r is sufficiently small
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Other strategies
trigger strategy: severe threat
� as usual - people forget or they do not want to be that harsh� others know that, thus to stick to the Nash after defection might not
be credible� we search for strategies that are less grimm than trigger strategies
stick and carrot
tit for tat
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Coordination on the collusive price
Which collusive price? → problem of coordination
� tacit collusion: costly experimentation to coordinate on a collusiveoutcome, risk of triggering price wars
� explicit collusion: firms coordinate on collusive outcome and avoidproblems due to shock adjustments
� market sharing schemes: possible to adjust to cost and demand shockswithout triggering price wars
� firms will try to talk in order to coordinate!
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Factors that facilitate collusion
Market structure
Price transparency and exchange of information
Pricing rules (facilitating practices)
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Market structure
Concentration: collusion is normally easier to maintain among few (andsimilar) firms
� πM
n (1 + δ + δ2 + . . .) = πM
n1
1−δ ≥ πM + 0� δ > 1 − 1
n
Entry: if entry barriers are high, collusion is easier to sustain
Cross-ownership: reduces incentives to cheat, hence facilitates collusion
Regularity and frequency of orders: allow for easy detection and timelypunishment, hence facilitate collusion
Buyer Power: strong buyers can play off rivals against each other →discourages collusion
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Market structure cont’d
Random shocks to demand: make it harder to detect deviation → discouragecollusion
Steady demand growth: makes punishment more effective → facilitatescollusion
Product homogeneity: has ambiguous effect on collusion
Symmetry: more equal distribution of assets facilitates collusion
Multi-market contacts: allow firms to leverage punishment into othermarkets, hence facilitating collusion
Inventories and excess capacity: have ambiguous effect on collusion
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Price transparency and exchange of information
observability of firms’ actions facilitate enforcement
� when prices are unobservable and demand is subject to shocks:deviation is difficult to identify → collusion more difficult (possiblyinvolving temporary “price wars”)
information exchange of past/present prices and quantities: detailed infolikely pro-collusive
� frequency auctions: simultaneous ascending auctions� code for a certain region = 02, then firms used a price like 1002 to
indicate their interest in this region� in Germany the auction design requested 10% increases when rasing
bids: Mannesmann signaled to share the market by bidding 18.8 millDM on blocks 1-5 and 20.0 mill DM on blocks 6-10 → why differentbids for equal products? as an answer, managers of T-Mobil increasedto 20.0 DM on the blocks 1-5
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Price transparency and exchange of information cont’d
public announcements
� Telekom Austria cited in the newspapers:� “it would be satisfied with 2 out of the 12 blocks of frequencies on
offer”, but “it would bid for a 3rd block if one of its rivals did”
“collusive price” is often ambiguous (may need to be adjusted from time totime) → exchange of information on future prices/quantities
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Pricing rules (facilitating practices)
Most favored nation (or most favored costumer) clause
� engages a seller to apply to a buyer the same conditions offered (by thesame seller) to other buyers
� engagement to not price discriminate → make it costly to give pricediscount
� collusion: harder to deviate and costly to carry punishment
Meeting-competition clauses
� if the buyer gets a better price from another seller, the current sellerwould match the price
� clause works as an information device and reduces incentive to deviate
Resale price maintenance
� vertical price agreement → vertical restraints and vertical mergers
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Practice: What should be legal and what illegal?
Standards of proof: market data vs. hard evidence
Ex-ante Competition policies against collusion
Ex-post Competition policies against collusion
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Standards of proof: market data vs. hard evidence
Inferring collusion from data
� price levels: what is a high prices? estimation price-cost marginswithout cost data
� evolution of prices: price parallelism is not a proof of collusion(common shocks)
� conclusion: econometric tests as complementary evidence, not proof ofcollusion (results sensitive to different techniques used)
Hard evidence
� communication on prices or coordination on facilitating practices� focus on observable elements verifiable in courts, to preserve legal
certainty: fax, e-mail, phone calls, video etc.
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Ex-ante competition policies against collusion
avoid formation of cartels
deterrence of collusion: close monitoring and high fines, possibly prisonsentences for managers (like US)
black list of facilitating practices might deter collusion and free resources forcartel detection
� private announcements of future prices/outputs� exchange of disaggregate current/past information
good auction design to avoid bid-rigging
merger control (joint dominance)
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Ex-post competition policies against collusion
surprise inspections (“Dawn Raids”)
� to find hard evidence of collusion
leniency programmes
� introduced in the US in 1978 (reformed in 1993), in EU in 1996
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Calculation of cartel damages
Main effects of a price fixing cartel
Methods to calculate “but for” prices
Pass on defense
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Main effects of a price fixing cartel
cartel overcharge harm: effect of higher prices on actual consumers
lost volume effect: effect of higher prices on lost consumers/loss of volume toactual consumers
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How are profits of consumers affected?
decomposition of profits of purchasing firm
� π = (p − c)q� Δπ = −qΔc + qΔp + (p − c)Δq
direct cost effect: overcharge times number of purchased quantity
pass on: depends on the extent to which the price increase caused by thecartel is passed along the supply chain
output effect: reduced profits as a lower quantity is sold
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Distribution of cartel overcharges
in 93% of the cases, overcharge in % of the cartel price is above zero
small but significant proportion of cartels with no overcharge
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Dynamic effects
market structure and market functioning
� reduction in rivalry between firms can result in lower levels ofinnovation
� slowing down in the rate at which improvements in efficiency areachieved
� inefficient firms do not leave market� distortions in the downstream markets due to higher input costs
consequences
� for example, the counterfactual price may have been even lower (andhence the overcharge even higher) if the market had seen cost-reducinginnovations in the absence of the cartel
� however, it may be difficult to demonstrate a causal link between theinfringement and the alleged longer-term harm
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Calculate the damages
calculation of the price-overcharge “rectangle”
� period of time during which the conspiracy had an effect on prices� prices at which the conspirators sold their output
� also relevant: prices of (non-conspiring) competitors of the conspirators,who might adjust their prices in the light of the conspirators’ prices
� “but for” prices that would have prevailed in the market in the absenceof the conspiracy
� should include the “but for” prices of the non-conspiring competitors
� the quantities sold by the conspirators during the period of theconspiracy
� the quantities sold by the non-conspiring competitors
calculation of the deadweight welfare loss “triangle” needs one further pieceof information
� price-elasticity of demand for the product
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Methods to calculate “but for” prices
comparator based methods and models
� before and after, yardstick� comparison of means, time series models, difference-in-difference� determinants of prices, forecasting
financial analysis based methods and models
� cost based analysis
market structure based methods and models
� theoretical/structural models� static vs. dynamic models
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Before and after
comparison of data on companies (or markets) involved in the antitrustinfringement in a particular period with data on the same companies (ormarkets) in a period without the violation
comparisons
� before and during; during and after; before, during and after� pre-infringement data is not contaminated by the cartel� time after the cartel is obviously most recent, but the unwinding of the
cartel is perhaps not over
we would like to measure deviations from the long-run equilibrium path
appropriate when cartel period is rather short and the cartel does not inducea change in the long-run equilibrium path
example: Grazer Fahrschulen
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Yardstick
cross-sectional comparator-based approach
similar markets with and without a cartel are compared
appropriate with local markets
however, where there is a risk that these comparable markets may also havebeen cartelized, other methods should be considered
in combination with time series data: difference-in-difference
example: Lombard cartel
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Comparison of means or regression analysis
a comparison of means across regions or firms is applicable if there is atreatment effect
treated and non-treated are otherwise the same, but for the treatment, i.e.,the cartel
regression analysis can account for differences in observables
� regions are not the similar, but differ in observable demandcharacteristics like population density
� Yi = α + βXi + δDi + εi
� similar considerations for firms
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Comparison of means or regression analysis
comparison over time
� ARIMA models: price data is forecasted using only past observations ofprice
� cointegration and VEC models: it is possible to account for demandand supply and other observables
difference-in-difference
� infringement vs. non-infringement market in addition to period beforeand during infringement
� variations across firms and time are exploited� damage estimate = (period during)i - (period before)i minus (period
during)ni - (period before)ni
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Regression analysis: determinants of prices
Dummy variable approach
� price = f(cartel, determinants like product characteristics)� data for different time periods or different regions� for the estimations all data is used
Residual approach
� price = f(determinants)� different time periods or different regions� for the estimations data of non-cartel regime is used and predicted for
the cartel regime
implicit assumption: coefficients of the determinants are constant overperiods or regions
hedonic pricing: coefficients capture demand and supply factors
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Bid-rigging in procurement auctions
procurement auctions: lowest bid wins
mechanism to collude
� division of the market� inflated bids� side payments
in any case, the expected winning bid will be higher
Porter and Zona (1999)
� research question: how can we detect cartels?� application: detecting cartels in the Ohio school milk market� econometric approach
� compare markets with collusion with control group: same time,different regions
� in which districts do firms submit bids?� how high are the submitted bids?
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Cost based approaches
average cost + competitive profit margin
estimation of competitive price based on past margins
cost: balance sheet data
profit margin: recover cost of capital to invest in the firm, includes risk
more applicable when parties involved are companies as opposed toindividual consumers
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Market structure based
based on an IO model the “but for” price is simulated
estimation of marginal cost, demand elasticity using data on prices andquantities
various static oligopoly models
� Bertrand competition� Cournot competition� Stackelberg model� Dominant firm model
dynamic considerations
� output decisions of today influence a firm’s cost structure in the futureby learning effects
� entry and exit in the industry
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Cournot model: competition in quantities
there are i = 1, . . . , n firms that maximize their profits πi
πi = p(q)qi − cqi
FOC: ∂p(q)∂q qi + p(q) − c = 0
Lerner index: p(q)−cp(q) = si
μ with si = qi
q and 1μ = −∂p(q)/p(q)
∂q/q
cartel overcharge
� factual is a cartel, i.e., a monopoly with firms maximizing joint profits:
m = p(q)−cp(q)
� counterfactual is an oligopoly with N firms: m(N − 1)/(N + 1)
the lost-volume effect triangle as a proportion of the overcharge rectangle isequal to (N − 1)/2(N + 1)
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Structural approach
Lerner index: p(q)−cp(q) = si
μ with si = qi
q and 1μ = −∂p(q)/p(q)
∂q/q
rewrite: μ p(q)−cp(q) = λ (elasticity adjusted Lerner index)
� λ = 0 for perfect competition� λ = 1
n for Cournot� λ = 1 for a cartel
estimation of marginal cost c using price and quantity data
inverse merger simulation that could also take changes in marginal cost intoaccount
if we also estimate λ, then we already now the extend of the cartel
Zulehner, Regulation and Antitrust 61 / 63
Moving from the factual/counterfactual to a final value
time period of the damage compared to the time period of the estimations
summation of losses over time, if the damages claim stretches over multipleyears
uprating and/or discounting cash flows to take into account the logic oftime value of money
interest from the time the damage occurred until the capital sum awarded isactually paid
consider taxes
Zulehner, Regulation and Antitrust 62 / 63
Pass-on defense
under which circumstances is it plausible that the overcharge was passed onto end-consumers
determinants
� a distinction must be made between firm-specific and industry-widecost increases
� what is the competitive environment
extend of pass-on
� low pass-on: firm-specific cost increase, i.e., only the defendant isconcerned, and high degree of competition
� high pass-on: under perfect competition, an overcharge that affects allcompetitors in a downstream market (industry-wide) would be passedon in full
� medium pass-on: high concentration and industry-wide cost increases
Zulehner, Regulation and Antitrust 63 / 63